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Research on Air Distribution Control Strategy of Supercritical Boiler

Author

Listed:
  • Yingai Jin

    (State Key Laboratory of Automotive Simulation and Control, Jilin University, Changchun 130022, China
    College of Automotive Engineering, Jilin University, Changchun 130022, China)

  • Yanwei Sun

    (State Key Laboratory of Automotive Simulation and Control, Jilin University, Changchun 130022, China
    College of Automotive Engineering, Jilin University, Changchun 130022, China)

  • Yuanbo Zhang

    (State Key Laboratory of Automotive Simulation and Control, Jilin University, Changchun 130022, China
    College of Automotive Engineering, Jilin University, Changchun 130022, China)

  • Zhipeng Jiang

    (State Key Laboratory of Automotive Simulation and Control, Jilin University, Changchun 130022, China
    College of Automotive Engineering, Jilin University, Changchun 130022, China)

Abstract

Supercritical boilers have become a major development trend in coal-fired power plants, and the air distribution strategy is a key factor in the design and operation of making it fully combustible. In this paper, the mathematical and physical models of a 350 MW supercritical boiler is established, and the optimal air distribution mode of the boiler at different load is determined based on the furnace outlet temperature, NO x concentration, and O 2 content. The air distribution control strategies were derived and the corresponding procedures were established. 160 MW and 280 MW were selected for positive pagoda and 180 MW and 230 MW for waist reduced. At 290–350 MW load, the effect of adjusting the combustion damper opening on the outlet oxygen is weak, so preferentially adjusting the SOFA damper opening can achieve better results. The results show good thermal efficiency and emission performance and are applicable to adjust the air distribution mode to achieve fuller combustion of supercritical boilers.

Suggested Citation

  • Yingai Jin & Yanwei Sun & Yuanbo Zhang & Zhipeng Jiang, 2022. "Research on Air Distribution Control Strategy of Supercritical Boiler," Energies, MDPI, vol. 16(1), pages 1-19, December.
    • Handle: RePEc:gam:jeners:v:16:y:2022:i:1:p:458-:d:1021722
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    References listed on IDEAS

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    1. Li Nie & Jiayi Lu & Qigang Deng & Liming Gong & Dayong Xue & Zhongzhi Yang & Xiaofeng Lu, 2022. "Study on the Uniformity of Secondary Air of a 660 MW Ultra-Supercritical CFB Boiler," Energies, MDPI, vol. 15(10), pages 1-12, May.
    2. Valentyna Stanytsina & Volodymyr Artemchuk & Olga Bogoslavska & Artur Zaporozhets & Antonina Kalinichenko & Jan Stebila & Valerii Havrysh & Dariusz Suszanowicz, 2022. "Fossil Fuel and Biofuel Boilers in Ukraine: Trends of Changes in Levelized Cost of Heat," Energies, MDPI, vol. 15(19), pages 1-18, September.
    3. Li, Sen & Xu, Tongmo & Hui, Shien & Wei, Xiaolin, 2009. "NOx emission and thermal efficiency of a 300Â MWe utility boiler retrofitted by air staging," Applied Energy, Elsevier, vol. 86(9), pages 1797-1803, September.
    4. Heming Dong & Yu Zhang & Qian Du & Jianmin Gao & Qi Shang & Dongdong Feng & Yudong Huang, 2022. "Generation and Emission Characteristics of Fine Particles Generated by Power Plant Circulating Fluidized Bed Boiler," Energies, MDPI, vol. 15(19), pages 1-13, September.
    5. Wang, Chunlin & Liu, Yang & Zheng, Song & Jiang, Aipeng, 2018. "Optimizing combustion of coal fired boilers for reducing NOx emission using Gaussian Process," Energy, Elsevier, vol. 153(C), pages 149-158.
    6. Wang, Yanhong & Li, Xiaoyu & Mao, Tianqin & Hu, Pengfei & Li, Xingcan & GuanWang,, 2022. "Mechanism modeling of optimal excess air coefficient for operating in coal fired boiler," Energy, Elsevier, vol. 261(PA).
    7. Horbaniuc, Bogdan & Marin, Ovidiu & Dumitraşcu, Gheorghe & Charon, Olivier, 2004. "Oxygen-enriched combustion in supercritical steam boilers," Energy, Elsevier, vol. 29(3), pages 427-448.
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